WO2020058383A1

WO2020058383A1 - Method and arrangement for determining haemodynamic parameters in a blood vessel in an automated manner on the basis of invasively recorded pulse waves

Info

Publication number: WO2020058383A1
Application number: PCT/EP2019/075127
Authority: WO
Inventors: Verena Dittrich; Chris Stockmann; Andreas Mainka
Original assignee: Redwave Medical GmbH
Priority date: 2018-09-19
Filing date: 2019-09-19
Publication date: 2020-03-26
Also published as: AU2019344027A1; DE102019125062A1

Abstract

The invention relates to a method for determining haemodynamic parameters in a blood vessel in an automated manner on the basis of invasively recorded pulse waves by analysis of said pulse waves and/or pulse waves selected from the totality, but at least one pulse wave. The invasive measurement and/or determination of the pulse wave parameters (PWPs), in particular the pulse wave velocity (PWV), is performed by the following method steps: introducing a pressure-measuring catheter having a pressure-measuring sensor as far as an intended measurement point within the blood vessel; recording and storing a temporal pressure curve and detecting a pulse wave signal at the measurement point; identifying and classifying the individual pulse waves from the pulse wave signal; analysing the pulse waves in respect of various properties, for example times, amplitudes, forms and/or relevant points; determining the PWV on the one hand by means of a wave decomposition method by determining and calculating a time offset with a given reference distance between a pulse-wave basic signal component and the pulse-wave echo component of the blood vessel system in the pulse wave signal; determining the PWV on the other hand by means of a wave analysis without dependency on the reference distance via a given pressure/flow model and a pressure/volume model of the blood vessel system.

Description

METHOD AND ARRANGEMENT FOR THE AUTOMATED DETERMINATION OF HEMODYNAMIC PARAMETERS IN A BLOOD VESSEL OF PULSE WAVES RECORDED INVASIVELY

DESCRIPTION

The invention relates to a method for the automated determination of hemodynamic parameters in a blood vessel on invasively recorded pulse waves by analyzing these pulse waves and / or pulse waves selected from the entirety, but at least one pulse wave according to claim 1.

A. Cardiovascular events strongly define human mortality worldwide. In order to identify the associated risk at an early stage and prevent such an event, numerous hemodynamic parameters are collected and evaluated. For example, the elasticity or stiffness of the arteries is an independent predictor of cardiovascular events

(Heart attack, stroke, death) and a promising opportunity

To be able to differentially assess risk persons, especially those with intermediate cardiovascular risk. The pulse wave velocity (PWV)

describes this vascular stiffness and is a proven, officially recognized parameter that is anchored in the ESH guidelines, for example.

B. In addition to pulse wave velocity (PWV), a large number of other known hemodynamic parameters play an important role in assessing the arterial condition of a person, for example the augmentation index, the augmentation pressure, the cardiac output or the PWV variability. This

Parameters make it possible, individually and / or from their entirety, to obtain specific information about the rigidity of the arterial wall of the vessel. In order to determine the parameters, pulse waves are different with regard to

Properties, e.g. B. times, amplitudes, shapes or relevant points are analyzed. All parameters generated from the analysis of pulse waves are to be referred to below as “pulse wave parameters” or “PWP”.

C. Various PWPs describe conclusions about the stiffness of the arterial vessel wall, symbolically the best known of these stands for this

Parameters, the pulse wave velocity (PWV). The evaluation of the stiffness of the arterial wall with the help of PWPs in turn provides information about structural Disorders of the arteries, some of which precede certain vascular changes and the other part of which develop in parallel.

A measurement of the stiffness of the arterial vessel wall which is customary as the gold standard according to the current state of the art comprises an invasive measurement of the PWV and further PWPs at two measurement points in the aorta with the aid of a cardiac catheter. In humans, the cardiac catheter is usually inserted through an access via the femoral artery (A. femoralis). There is then a recording of pressure waves, which are caused by the regular contraction of the heart, at two points invasively in the blood vessel,

for example, first in the ascending aorta (ascending artery) and second, after the catheter has been withdrawn in the direction of the aortic fork

(Bifurcation) in right and left leg arteries. An ECG is often, but not always, registered at the same time.

The further procedure is usually as follows: The time difference between the R wave in the registered ECG and the base point of the pressure wave registered via the catheter results in a so-called transit time (TT). The transit time describes the time required for the pressure wave to travel from the contraction of the heart to the respective measuring point. The difference in transit times at the first measurement point and at the second

The measuring point then gives the running time of the pressure waves between the first

Measuring point and the second measuring point. The distance between the first measuring point and the second measuring point is determined by withdrawing the catheter from the blood vessel, the withdrawal length of which being recorded. The PWV in the blood vessel can then be determined from the detected transit time difference at the two measuring points and the withdrawal length of the catheter.

D. Due to the high volatile fluctuations of the PWV and other PWPs, regular measurements on the persons concerned are recommended. For such measurements, non-invasive measuring systems are required, which are used in everyday life, outside of a catheter laboratory and sometimes also outside of a doctor's office. Non-invasive measurement systems, however, require validation, which can only be achieved by invasive measurements as described. However, the invasive measurement method is increasingly changing. For cardiac catheter examinations, access via the

Wrist artery (radial artery) selected. For anatomical and technical reasons, however, the invasive determination of the PWV and some other PWPs is not possible by withdrawing the catheter. However, this means that future non-invasive systems cannot be validated invasively, or only with great effort, since the withdrawal method is a prerequisite for this, but is increasingly being used less.

In addition, studies showed a high interoperator variability in the manual evaluation of the invasive pressure curves using the retraction method. This means that the measured PWV and other PWPs are heavily dependent on the individual execution of the measurement. The reason for this are both fluctuations in the hemodynamics during the sequential measurement with withdrawal, as well as the time measurement between the ECG as the starting point and the pulse wave as the end point, which is partly due to fluctuations in the pre-ejection period (PEP, PEP, Variability). As a result, the objectivity and accuracy of the measured PWV is restricted even with the gold standard mentioned.

In addition, there is the comparatively high effort of the manual evaluation.

This ties up expensive personnel and is an additional source of error.

In addition, the withdrawal length (i.e. the distance from the measuring point in the ascending artery to the bifurcation) and the measuring points must be measured or determined as precisely as possible. This is often only possible to an insufficient extent under real measurement conditions.

E. There is therefore the task of a method for automated

Determination of hemodynamic parameters in a blood vessel on invasively recorded pulse waves by analyzing these pulse waves and / or pulse waves selected from the totality, but at least one pulse wave

specify in which an invasive measurement of the PWPs, in particular the PWV, in a simple manner, without a retraction method, with minimization possible

Sources of error and can be executed with high accuracy. The evaluation should take place automatically and should therefore be easy, quick and delegable. The interoperator variability of the measurement process is to be reduced and thus the objectivity of the measurement is increased. Furthermore, the Accuracy of the invasive gold standard method can be increased.

Finally, a future-proof validation option for others

non-invasive systems for determining the PWPs are created.

The task is solved with an automated method

Determining hemodynamic parameters in a blood vessel on invasively recorded pulse waves by analyzing these pulse waves and / or pulse waves selected from the totality, but at least one pulse wave with the features of claim 1. The subclaims contain expedient or advantageous embodiments of the method.

As an example for all PWPs, the method for invasively measuring a pulse wave velocity in a blood vessel is carried out with the following method steps:

A pressure measuring catheter with a pressure measuring sensor is inserted up to a designated measuring point within the blood vessel. This is followed by recording and storing a pressure curve over time and recording at least one pulse wave signal at this measuring point.

In a next method step, at least one pulse wave signal is analyzed to determine the PWPs, hereinafter using the example of the PWV. This is done in at least two different ways, which can also be combined if necessary, and to make the determination more robust:

For one, z. B. a so-called wave separation method (wave separation) applied. By extracting a pulse wave echo component from at least one pulse wave signal, a time offset between one

Pulse wave fundamental signal component and the pulse wave echo component determined in the pulse wave signal. This time offset is given by means of a

A PWV is calculated from the reference distance between an echo point of the blood vessel system and the position of the pressure measurement sensor in the blood vessel system.

On the other hand, a PWV z. B. determined with the help of the so-called wave analysis. In particular, the models of the Bramwell-Hill model and a given pressure / flow model of the blood vessel system have proven to be suitable, but are not limited to this. The basic idea of the method is therefore to determine the pressure profile over time

Record the blood vessel at only a single measuring point in the blood vessel and then record the pressure curve recorded in an automated manner

To supply signal processing. It is also essential to the invention to separate an echo signal from the recorded pressure curve, which is generated in the course of the blood vessel system itself. This echo signal is then converted into a time offset from which the PWV can be determined directly. It is also essential to the invention that an analysis with regard to the at least one pulse wave recorded at the single measuring point

Determination of relevant points and areas on the signal to determine further PWPs, e.g. B. the augmentation index, augmentation pressure and cardiac output is performed.

In an advantageous embodiment of the method, a signal filtering of the stored temporal pressure curve is carried out using a high and / or a low pass filter to detect the pulse wave signal. Signal components in the pressure curve caused by interference or outside of a typical

assumed frequency range are filtered out and are not included in the subsequent signal processing.

Advantageously, a occurs when the pulse wave signal is detected

Classification of detected individual pulse waves, with a base point detection for identifying each individual pulse wave being carried out in a first step and a signal analysis for determining physiologically relevant signal points being carried out on the individual pulse wave in a second step. As a result, the shapes of the signal curve can be taken into account and in the

include the following evaluation.

The extraction of the pulse wave echo component according to the wave decomposition method takes place in an advantageous embodiment such that the classified pulse wave is broken down into a forward signal component and a backward signal component on the detected pulse waves to extract the pulse wave echo component. The forward signal component is the basic pulse wave signal, while the reverse signal component is the pulse wave echo signal.

It is expedient to distinguish between the forward signal component and the

Reverse signal component determines a time difference as a time offset. The time difference can be determined via the identified base points of the basic pulse wave signal and the pulse wave echo signal or via the cross-correlation method.

In one embodiment, a reflection distance related to a body size to a prominent point that generates a pressure echo within the blood vessel system can be used as the given reference distance.

In addition, a weighted PWV can be determined from the PWV value determined via the wave decomposition method with the PWV value determined via the wave analysis.

The method steps are advantageously platform-independent

executed, an approximation to a standard resolution using a variation of the sampling rates of the pressure curve and the pulse wave signal

Comparability between different device-dependent recording techniques is realized.

An arrangement for executing a method according to one of the preceding claims comprises a measurement sensor which can be inserted and placed in the blood vessel, an evaluation and storage unit for receiving, storing and processing the data of the pressure data recorded by the measurement sensor and a control implemented in the evaluation and control unit - and

Evaluation program.

With an appropriate design, the measurement sensor is considered an indirect one

Measuring sensor from an invasively insertable into the blood vessel and filled with a fluid and a catheter located outside the blood vessel

Pressure transducer trained.

The evaluation and control unit can also have an interface for connecting an EKG detection device. In this way, the pulse wave data can be monitored and evaluated together with EKG data. The evaluation and control unit can expediently be a

Have a selection option for triggering a calibration and calibration process and / or for coordination with a measuring unit to be connected.

Examples which are expedient or advantageous are given below

Embodiments of the method and the device specified. For

Figures 1 to 10 serve to illustrate this.

An apparatus and a method for determining pulse wave parameters (PWPs), in particular the pulse wave velocity (PWV) on invasively recorded pulse waves, are explained below.

The basic principle of the method is a so-called single-point measurement carried out at only one location. During the measurement, the temporal signal curve of the pressure at the measuring point is recorded and evaluated. The aim of the method is to determine and evaluate a pulse wave echo, which results from the interaction of blood flow, blood pressure and the course of the arteries, e.g. from the aortic bifurcation located downstream of the body with the aorta forking into the left and right femoral artery. In principle, this is done in such a way that a number of parameters, e.g. B. a number of functions and support points and their intervals can be determined. So z. B. at a known reflection distance using the determined time intervals on the PWV.

The method is carried out, for example, using the following basic method steps, which are explained in more detail below. An invasive measurement in an arterial blood vessel is assumed here as an example.

In a first step, pressure curves over time are measured. These pressure curves over time represent arterial pressure curves. For this purpose, these pressure curves are recorded and stored in a human artery using a measuring unit. The pressure curve measurement is carried out invasively.

The measuring process takes place, for example, in such a way that in connection with a

Cardiac catheterization access via the artery on the wrist (A.

Radialis) and the pressure measuring sensor is pushed into a certain place in the artery. However, the procedure is fundamentally not based on restricted this particular access, but can in principle be carried out via any arterial access.

At least one pressure curve course, i.e. a pulse wave recorded. However, it is advisable to record several pressure curves over a certain time interval. The length of this time interval can be 10 seconds, for example.

In a next step, the recorded temporal

The individual pulse wave signals are extracted from pressure curves. This is done with the following steps:

If the pressure measuring sensor is placed in the desired position in the artery (e.g. in the Ascendens artery), the signals are stored with the pressure fluctuations, i.e. with the pressure profiles. The recorded signals are first cleaned of interference by filters. For example, high-pass and / or low-pass filters can be used for this purpose. The frequencies of 0.5 Hz for the high-pass filter and 50 Hz for the low-pass filter have been found to be suitable, but are not limited to this. The individual pulse wave signals,

in particular their start and end, recorded automatically in the pressure profiles. For example, the base point method, e.g. B. using the intersecting tangent method or the upstroke method. However, it is

Determining the pulse waves is not limited to these methods. The detected base points of the pulse waves are important parameters when determining the pulse wave speed.

The detected pulse waves are then classified. The shape of the individual pulse waves is analyzed. This allows a classification in at least one class, which has a significant influence on the

class-related further processing of the signals.

In a next step, a signal analysis is carried out on the classified pulse wave signals. Class-specific physiological points and properties of the pulse wave signal are determined, such as ejection duration ED (heart ejection time), a so-called inflection point IP (arrival of the reflected wave) or a characteristic impedance Zc (wave resistance). The points PI (First Shoulder) and P2 (Second Shoulder) have emerged as useful support points for the classification. The empirical wavelet transform (EWT) together with differentiation and Fourier transforms are particularly suitable for signal analysis. Dynamic time equalization (DTW) has proven to be particularly suitable for the classification. However, the analysis steps described are not limited to these methods.

These classified pulse wave signals are used for the

Wave decomposition methods each determine a pulse wave basic signal component and a pulse wave echo component, whose time offset from one another is determined.

Both signal components can be determined and the pulse wave echo component can be extracted, for example, by determining a so-called flow curve. This flow curve can be used statistically averaged, for example, as a triangle starting at the base point (F), the maximum at the inflection point (IP) and the end at the level of ejection duration ED. A more robust method is the so-called reservoir excess model. The excess curve determined can be used as a flow curve. Subsequently, the classified

Pulse waves into the respective forward waves (after ejection), i.e. in the forward signal component and the backward waves (after reflection on the vessel walls and vessel branches), i.e. into the reverse signal component.

The forward signal component is then the pulse wave basic signal component, the

The reverse signal component then represents the pulse wave echo component in the individual pulse wave signal. In the next step, the time difference between the

Pulse wave fundamental signal component and the pulse wave echo signal component, determined. The time difference can be determined using the identified footpoints of the

Pulse wave basic signal and the pulse wave echo signal take place. The method of cross correlation, which is caused by shifting the two signals

Pulse wave basic signal and the pulse wave echo signal in each other determines the time difference, however, has proven to be more robust.

To use the wave decomposition method z. B. to determine a PWV, the determination or determination of a length is required. This length forms a reference distance for the determination of the PWV and goes as Evaluation parameters in the signal processing. In particular, this is the distance between the position of the pressure measurement sensor and the echo point in the blood vessel system, which causes the pulse wave echo signal component.

This reference distance can either be measured and then leads to the specification, in particular, of an arterial length, which is used as suitable for the reflection. However, it can also be used e.g. B. determine an effective reflection distance (EfRD) based on the body size of the person examined.

Alternatively, the PWV can be determined by using the wave analysis without specifying a distance. The models of the

Bramwell-Hill model and a pressure / flow model of the blood vessel system have been found to be suitable, but are not limited to this. This means that the determination of the retreat length can be omitted. The relationship between volume and pressure (PV relation) reflects, for example, the so-called arterial compliance, which is required in the Bramwell-Hill model. With the help of the PU loop, which reflects the relationship between the flow velocity and the pressure in the artery, the PWV can be derived at a local point via the increase at the beginning. The Korteweg equation, which takes into account the dependency of blood pressure via the elasticity module of the blood vessel wall, is also suitable.

All approaches, such as the wave decomposition process described below

Inclusion of the length and the wave analysis, which is independent of the length, can then be viewed together, whereby the PWV is determined independently of one another with different approaches (fusion approach). The results can then be weighted against each other so that the final pulse wave velocity best corresponds to the real PWV.

The method is advantageously carried out independently of the platform.

For example, by sampling the sampling rate and approximating to a standard resolution, comparability between different recordings (ie in particular different patients) and different measuring units (such as different types of catheters, so-called smart stents) and the like other measurement sensors) achieved become. The values of 1,000 Hz and 12 bits have proven to be suitable

, but are not limited to this.

The following arrangement is expedient for carrying out the method, the characteristics of which are also explained below using examples:

A measuring unit is provided. The measuring unit consists of a

Measuring sensor, which is connected to a control and storage unit. This measuring sensor can be used directly or indirectly invasively and placed at the desired location in the artery. One embodiment provides that a liquid-filled catheter with access via the radial artery is placed in the ascending artery and connected to a pressure sensor. The pressure domes belonging to the catheter and the control and storage unit are located outside the measuring point, i.e. especially outside of the body. Optionally, an EKG detection device

be provided, via which an EKG (an electrocardiogram) can be written and stored in parallel.

Furthermore, a control and evaluation program is provided, which the

described steps for processing, processing and evaluating the stored pressure signals automatically.

An interface for exporting the data can also be provided, as can a GUI interface for displaying the information, such as, for example, the pressure signals and certain parameters, such as, for. B. the foot points PO, the transit time TT, the ejection time of the heart ED, the inflection point IP, the pulse wave peaks z. B. PI and PI and / or the wave resistance Zc. An interface for performing updates is also useful.

In addition, in one embodiment, a switch for calibration or

Calibration of the measuring system should be provided before each measurement (e.g.

Pressure calibration). In addition, depending on the measuring unit used (catheter, smart stent and such devices), an individual determination of the damping coefficient and the resonance frequency is useful.

The method mentioned and the example arrangement described are used for extracting and analyzing aortic pulse waves and for determining hemodynamic parameters (PWPs) of pulse wave analysis, such as B.

Pulse wave speed used.

The method and the arrangement are additionally explained below with reference to the attached figures.

It shows:

1 shows an exemplary basic configuration of the measuring arrangement,

Fig. 2 shows an exemplary measured pressure curve in a blood vessel

3 is an illustration of the base point method,

Fig. 4 is an illustration of individual, detected over the base points

Pulse waves,

5 shows a basic representation of different signal components in a single pulse wave signal,

6, 7 and 8 each show an example of possible classifications of the pulse waveforms,

Fig. 9 shows an exemplary representation of prominent points in a

Pulse wave,

Fig. 10 shows an exemplary wave decomposition of a pulse wave in the

Signal analysis.

1 shows a basic configuration for an arrangement for carrying out the method. The arrangement includes a catheter 1, a pressure sensor 2 and a control and storage unit 3. The catheter 1 and

Pressure sensors form a measuring sensor unit. In the example given here, it is used indirectly invasively and placed at the desired location in the artery. One embodiment provides that a

liquid-filled catheter 1 with access via the radial artery 4 placed in the ascending artery 5 and connected to the external pressure transducer 2 becomes. The pressure sensor 2 associated with the catheter and the control and storage unit 3 are located outside the measurement point, ie in particular outside the body. Optionally, an EKG detection device 6 can be provided, via which an EKG (an electrocardiogram) is parallel

can be recorded and saved.

Furthermore, a control and evaluation program 7 can be provided, which carries out the steps described in the method for processing, processing and evaluating the stored pressure signals. The tax and

Evaluation program can be imported and updated externally in the evaluation and control unit.

An interface 8 can also be provided for carrying out updates. In addition, an interface 9 for exporting the data is useful, as is a device-internal or external GUI interface for a display 10 or an external evaluation unit 11, for example a PC, with an external evaluation program 12 for displaying the information, such as, for example, the pressure signals and certain parameters, such as B. determined foot points F, a transit time TT, an ejection time of the heart ED, an inflection point IP and / or the support points of pulse wave peaks such. B. PI and P2.

In addition, in one embodiment, a switch 13 can be provided with which a procedure for calibrating or for calibrating the measuring system can be triggered before each measurement. This applies in particular to pressure calibration. In addition, when designing the control and evaluation program, a procedure makes sense with which the damping coefficients differ

Have the design of the measuring unit used determined. In this way, the properties of catheters, a so-called smart stent and other components can be taken into account when evaluating signals. An individual determination of the damping coefficient and the resonance frequencies of the above-mentioned components can thus be carried out and is useful in terms of measurement technology.

2 shows the raw data initially acquired by the method. A pressure curve as a function of time is shown here. These signals are registered at the measuring point by the pressure sensor and by the storage unit

recorded. Withdrawal and simultaneous registration of an EKG are not necessary. The data can also z. B. about the access of the A. Radialis raised and without the influence of the R peaks of the EKG

originating PEP variability can be evaluated. PEP variability is understood to mean fluctuations in the time between the electrical excitation of the heart (R peak in the ECG) and the actual start of ejection (foot point). This scatter leads to a blur in the PWV determination by the withdrawal method

The signal should be recorded in a sufficient resolution and sampling rate so that details in the pulse waves are retained. A sampling rate of 1,000 Hz and a processing width of 12 bits have been found to be suitable, but these parameters are not limited to this.

Both the sampling rate and the resolution are not fixed per se, but rather only device-specific sizes. In order to ensure platform independence and thus the best possible processability, the measured value quantity of the temporal pressure curve is then transformed either in the control and storage unit itself or in the external evaluation unit to a uniform standard so that its processing

platform independent and thus unified. For this purpose, the signal of the temporal pressure curve can, for example, be sampled up to a sampling frequency of 1,000 Hz. For this sampling process you can

different approximation methods are used. In particular, z. B. the so-called cubic spline approximation used. With this approximation, two neighboring sample points are approximated.

For cubic spline approximation, polynomials of degree 3 are determined for two neighboring sample points (xi, y and (x; _{+ i} , y; _{+ i} ):

s _t (x) = a _έ + fc _j (x— c _έ ) + C _j Cx— c _έ ) ² + d _j (x— jC _j ) ³

This applies because of the continuity of the signal to be sampled

Continuity requirement Si (x _{i + i} ) = Si + i (xi + i), where s has to be continuously differentiable twice:

Si ^, (Xi ₊ l) = S _{i +} l ^, (Xi ₊ l) ^Si, (Xi ₊ l) = Si ₊ ^l, (x _{i +} l)

When a new hx is selected, the signal can be resampled. If the output signal is sampled to a sampling frequency of 1,000 Hz, the following applies in this case:

The choice of the type of splints with regard to the edges does not play a decisive role.

Signal interference can be eliminated by using suitable filters. The recorded signals are first cleaned of interference by filters. For example, high-pass and low-pass filters can be used for this. The frequencies of 0.5 Hz for the high-pass filter and 50 Hz for the low-pass filter have been found to be suitable, but are not limited to this.

Then the individual cardiac cycles, i.e. the individual pulse wave signals, in particular their start and end, are identified and extracted. Carrying out the first time derivative with a subsequent determination of the base point has turned out to be suitable, but is not limited to this.

3 illustrates the footpoint method "intersecting tangent" used in the method for extracting the individual pulse waves PW from the signal curve. In the footpoint method described here by way of example, all turning points w (i) in the signal curve are determined with a positive increase in the first derivation from the fact that the value of the first temporal derivation of the pressure curve PPW is extremal in its place:

The variable w denotes the respective positions of the "positive"

Turning points on the timeline. The result is a set of all the determined peaks, ie peaks, within the pulse-like signal component. Starting from the inflection point determined in each case, the base points F of the individual pulse waves PW are located, for example, with the aid of intersecting tangents in the vicinity of each individual maximum in the 1st derivative, that is to say in the vicinity of the previously determined inflection point. In addition to the determined tangent t _w at the turning point w (i), the first local minimum M in the time range before the individual pulse wave is sought. This local minimum M has a horizontal tangent t _M. Then the intersection S between the horizontal tangent t _M and the regression line, ie the tangent t _{w, is} calculated. This intersection point S, projected onto the signal curve, is then the base point F of the pulse wave PW. This point can also be adjusted subsequently.

Fig. 4 shows the correspondingly extracted pulse waves PW in the registered

Pressure history. These are separated from one another by the base points F and identified.

Then all peaks of the 1st derivative are sorted by size in descending order.

s is the sorted sequence of the determined turning points.

This sorted sequence of peaks is analyzed step by step. Each peak is then recorded as a turning point relevant for the signal evaluation if its minimum height is greater than 0 and if its distance from all turning points already detected is greater than a defined time interval with respect to a predetermined sample rate FS.

Each peak w (i) from the sequence s (i) is therefore a turning point idx if the following conditions (a) and (b) are fulfilled at the same time:

(a) s (i)> 0 and 1,000> D _r with j <i

Condition (b) expresses that a peak w (i) must have a certain minimum distance D from a peak idx (j) that has already been identified. This minimum distance is independent of the sample rate. In the present example, this is, for example, 350 ms.

A subsequent ascending sorting of idx puts the indices in the correct chronological order.

In order to avoid any noise and minor interference in the signal and even more so when differentiating, the 1st derivative can be calculated using the "Savitzsky-Goley" method.

The location of their respective base points is of crucial importance for the identification of the individual pulse wave in the pulsating signal component. As already described, these can be determined from the turning points.

The following applies for each base point F with the coordinates F _j (x, y)

X _j = idx (j) - i gap where gap is the respective gap in the samples, and y, = PPW (X _I ) with i = l, ..., n the regression points next to the inflection point idx (j ). Where n is the number of regression points. Based on the coordinates (x ,, y,) of the base points F _j , coefficients a, b of a straight line equation g (x) = ax + b can now be determined.

The pulse wave signals PW thus extracted are subsequently analyzed further. The essential core of the signal processing is the separation of the individual pulse wave signal PW into a pulse wave basic signal PG and into one

Pulse wave echo signal PE.

FIG. 5 shows the basic principle of the wave decomposition method of the individual extracted pulse wave signal PW into the pulse wave basic signal PG and the pulse wave echo signal PE. The pulse wave signal PG describes the

Pressure curve of the pulse wave signal, which would occur if the blood vessel had no echo point. At the echo point of the blood vessel, however, the pulse wave is partially reflected and is at the location of the invasive pressure measurement Pulse wave echo signal PE can be registered. Both signal components have a time offset T from one another. This time offset allows one, for example

Conclusion on the pulse wave velocity PWV between the location of the invasive pressure measurement and the known echo point in the blood vessel system.

In addition to determining the PWV by breaking it down into the basic pulse wave signal and the pulse wave echo signal, the shape of the pulse wave signals can be further analyzed and classified.

Figures 6, 7 and 8 show examples of different categories of

Pulse waves. These differ in particular in their form. The pulse waves are classified accordingly. Decisive for the classification are the different forms in the course of each individual pulse wave signal PW, or the existence of points and features of a first shoulder PI and a second shoulder P2 of each individual pulse peak, as well as a strength of a dicrotia or incision I of the respective pulse wave.

In the classification, the first and the second shoulder of each individual pulse wave peak in each individual pulse wave individual signal describe the strength of the "double summit" of a peak. It describes the change in the

Pulse wave due to the arrival of a reflected wave. This reflected component is the pulse wave echo component. The so-called Inflection Point IP is located between the double peaks of the pulse wave signal. The correct position of IP has z. B. the wave decomposition experience a high impact on the determined PWV. The speed at which the pulse wave echo is reflected and thus the time interval between the support points PI and P2

thus describes how "round" the individual period, ie the individual pulse wave, is in its course and how strongly the individual pulse wave signal deviates from the round shape. If the pulse wave echo returns very quickly due to a stiffened blood vessel system, a double peak can be determined. Here, the amplitude of PI is usually lower than that of P2.If the pulse wave echo returns particularly slowly, one speaks of a double peak, but here PI is higher than P2.The mixed form between these two forms can be observed, which has only one peak .

Based on this, each individual pulse wave can be classified into form classes. The number of calculation functions, i.e. the number of classes, is k, where k is a natural number greater than 0. The assignment to a class can be made according to the "nearest neighbor" principle. For example, the one belonging to a pulse wave

Pulse wave individual signal PW have a left shoulder, while a first calculation function of class k = 1 has no left shoulder and a second calculation function of class k = 2 has a left shoulder. The shape of the individual pulse wave differs from the shoulderless calculation function more than from that

Calculation function with the left shoulder. The pulse wave PW thus belongs to class k = 2, for example, and is thus represented by the calculation function of class k = 2. The class specification thus specifies which functions, which are classified according to certain properties, profiles or symmetries, must be used in order to “fit” the individual pulse wave signal.

The classification according to function types is not the only one

Classification possibility. Another possibility to assign to a class is to carry out the similarity analysis with the help of a dynamic time equalization (DTW). The period lengths of the individual pulse wave signals and their times are designed to be invariant and thus enable a comparison. This comparison makes the forms of the pulse waves comparable with one another and with respect to the calculation functions and can be assigned to the classes.

A class-specific algorithm can be specified for each of these classes, which determines the hemodynamic parameters for the class. For example, the pulse wave signals shown in FIGS. 6, 7 and 8 can be categorized into three different classes.

The pulse wave single signals PW of the pulse wave signals in Fig. 6 are e.g.

two peaks, the low peak PI on the left has a shoulder and the closest peak P2 has a significantly higher amplitude. Incision I clearly describes the end of expectoration from the heart. This

For example, pulse waveforms belong to a class of one

Function set of type k = 1 listened.

The individual pulse wave signals of the pulse wave signals in FIG. 7 are e.g. B. also two peaks with a peak PI and a peak P2 and a minimum located between them. The characteristics of the amplitude of the peaks PI and P2 have interchanged in comparison to the embodiment in Fig. 6. The peak PI now has a higher amplitude than P2. Incision I clearly describes the end of expectoration from the heart. This pulse waveform can therefore

Function set can be assigned to a class of type k = 2.

The individual pulse wave signals of the pulse wave signals in FIG. 8 are e.g. B. single-peaked and do not have clear peaks for PI and P2. Due to the

Shifting the pulse wave echo and the resulting increase in the total amplitude of the pulse wave PW in this embodiment the positions for PI and P2 are hidden in the pulse wave PW. Incision I clearly describes the end of expectoration from the heart. This pulse waveform can therefore

For example, a function set of a class of type k = 3 can be assigned.

To avoid discontinuities in the transformation, the

Intermediate areas between classes kept smooth. This means that if, for example, a pulse wave can be assigned to two classes, each of these two classes is treated as equally likely.

If, for example, a pulse wave PW is a little closer to one of these classes, the assignment is clear. The following then applies to a coefficient c: c = aCi + (1 - tr) c _{i + 1} , a = [0.1]

Here, c and Ci _{+ i are} the coefficients of the two nearest neighbors.

FIG. 9 shows an exemplary representation of shape features which are detected on a single pulse wave signal by function classes and which can thus be classified. It shows an exemplary representation of a pulse wave with the points F (base point), PI, P2, IP (inflection point; arrival of the reflected wave) and ED (ejection duration; ejection time of the heart; F to incisal I). These class-specific physiological points and properties are among others determined in the signal and serve as useful support in determining the pulse wave velocity and the PWPs.

The points PI (First Shoulder) and P2 (Second Shoulder) have proven to be useful support points. For the classification of the individual pulse wave signal and The so-called dynamic time equalization (DTW), together with a cluster analysis and a Fourier transformation, has proven suitable for its translation into a set of classified individual functions

exposed. However, the signal processing is not limited to this.

10 shows an example of the wave decomposition method for determining the ejected and reflected pulse wave. The pulse wave ejected here is the above-mentioned pulse wave basic signal component PG and the reflected pulse wave is the pulse wave echo component PE. In addition to this information, the so-called flow curve and the curve of the so-called reservoir pressure can also be determined and shown here. The reservoir pressure curve RP is calculated from the Ascendens pressure curve AP using a reservoir excess model based on the 3-element wind boiler model. The flow curve FLW (Flow) is obtained by subtracting the reservoir pressure curve RP from the Ascendens curve AP. A forward wave FW (P _f ) and a backward wave BW (P _b ) are separated by means of the flow curve (Q) and the ascendent curve (P). The values Q of the flow curve and the Ascendens curve P depend on the values P _{f of} the

Forward wave and the values P _{b of} the backward wave via the following

Relationships together:

P + z - Q

p _.

2nd

P - z - ö

p _ i

b 2

The size z is a characteristic impedance of the blood vessel and serves as a scaling coefficient of the flow curve Q. The backward wave BW is the returning component of the pulse wave reflected at an echo point in the blood vessel, the forward wave FW is the result of the amount of blood expelled from the heart in the blood vessel Flow direction moving component of the pulse wave. The Forward Wave FW represents the forward signal component of the

Pulse wave signal, the backward wave BW represents the reverse signal component of the pulse wave signal PW.

A so-called transit time TT can be determined in different ways. Firstly, the difference in the base points between the backward wave and the forward wave. Since the base points in the backward wave only Cross-correlation is a suitable alternative.

The TT represents the required degree of shift of the backward wave towards the forward wave. Dynamic time equalization (DTW) has proven to be suitable. Another method for determining the TT can be determined via the time interval between the first zero crossings of the averaged forward and backward wave.

The “mean” function here means that the mean value for the forward wave Pf and the backward wave Pb are calculated and then subtracted from the overall signal Pb or Pf. The signal thus swings around the value zero Zero crossings are then used to determine the TT.

The length of the blood vessel for determining the PWV, for example the aortic length, is measured independently. Alternatively, this can also be estimated using the following formula. The aortic length (distance) in relation to the height of the person (height) results from the

empirical anatomical relationship:

The pulse wave speed PWV then results from the aortic length

(Distance) and the previously determined transit time TT to:

Another approach to determine the PWV after the wave analysis can be done using the so-called Moens-Korteweg equation:

E _{inc is} the modulus of elasticity of the wall of the blood vessel, h the wall thickness of the blood vessel, r the clear radius of the blood vessel lumen and p the density of the blood fluid.

The modulus of elasticity E _ine results as follows: pb - SBP

Cmc - ^E 0 ^B

E ₀ corresponds to E _inc at an initial pressure of zero. SBP corresponds to the systolic blood pressure, which is derived from the higher the amplitude of the respective pulse wave.

All approaches, both the wave decomposition method including the length and the wave analysis, which is independent of the length, can then be considered together, because the PWV is included

different approaches determined several times independently (fusion approach). The results can then be weighted against each other so that the final pulse wave velocity best corresponds to the real PWV.

The method according to the invention was explained using exemplary embodiments. There are more in the context of professional action

Embodiments and modifications possible. Further exemplary embodiments also result from the subclaims.

Reference list

1 pressure measuring catheter

2 pressure measuring sensor

3 control and storage unit

4 access (e.g. A. Radialis)

5 measurement location (e.g. A. Ascendes)

6 EKG

7 Control and evaluation program

8 interface (for updates)

9 Interface for exports and GUI

10 display

11 external evaluation unit 12 external evaluation program

13 Calibration / calibration switch AP Ascendens-Pressure curve

BW backward wave

ED ejection time

FLW Klow curve

FW Forward Wave

F base

I incisor

M first local minimum

PI first partial peak

P2 second partial peak

PE pulse wave echo signal

PG basic pulse wave signal

PW pulse wave

PWV pulse wave speed

RP reservoir pressure curve

S intersection

T time offset

TT transit time

t _M horizontal tangent at the minimum t _w Tangent at the turning point

Claims

EXPECTATIONS

1. Procedure for the automated determination of hemodynamic

Parameters in a blood vessel on invasively recorded pulse waves by analyzing these pulse waves and / or pulse waves selected from the totality, but at least one pulse wave, with the method steps

- Inserting a pressure measuring catheter (1) with a pressure measuring sensor (2) up to an intended measuring point within the blood vessel,

- Record and save a chronological pressure curve and

Detecting at least one pulse wave signal (PW) at the measuring point,

- Extracting a pulse wave echo component (PE) from the at least one pulse wave signal (PW) and determining a time offset (T) between a pulse wave basic signal component (PG) and the

Pulse wave echo component (PE) in the pulse wave signal (PW),

- Converting the time offset (T) into a pulse wave velocity (PWV) using a given reference distance between an echo point of the blood vessel system and the position of the

Pressure measurement sensor in the blood vessel and / or

- Determination of in particular a pulse wave velocity (PWV) without taking into account a reference distance via a given pressure / flow model and a pressure / volume model of the

Blood vessel system.

2. The method according to claim 1,

characterized in that

to detect the pulse wave signal (PW), the stored temporal pressure curve is filtered using a high and / or a low pass filter.

3. The method according to claim 1 or 2,

characterized in that

when the pulse wave signal (PW) is detected, individual pulse waves are classified, with in a first step each individual pulse wave being identified, in particular by a

Footpoint detection takes place and in a second step on the individual Pulse wave a signal analysis for determining physiologically relevant signal points is carried out.

4. The method according to any one of the preceding claims,

characterized in that

on the detected pulse waves (PW) for extracting the pulse wave echo component, the classified pulse wave is broken down into a forward signal component (FW) and a reverse signal component (BW), the

Forward signal component (FW) is the pulse wave basic signal (PG) and the reverse signal component (BW) is the pulse wave echo signal (PE).

5. The method according to claim 4,

characterized in that

a time difference between the forward signal component (FW) and the backward signal component (BW) is determined as a time offset.

6. The method according to claim 5,

characterized in that

the time difference over the distance of the base points of the

Pulse wave basic signal and the pulse wave echo, or via a

Cross correlation is determined, the displacement of the two signals pulse wave basic signal (PG) and the pulse wave echo signal (PE) describes the time difference, or over the distance between the signals

Zero crossings of the averaged signals of the pulse wave basic signal (PG) and the pulse wave echo signal (PE) is determined.

7. The method according to claim 1,

characterized in that

a reflection distance related to a body size to a point within the blood vessel system that generates a pressure echo is used as the given reference distance.

8. The method according to claim 1,

characterized in that

for the hemodynamic parameter to be determined, in particular the pulse wave velocity (PWV), or intermediate steps for determining the hemodynamic parameter which is for individual pulse waves an averaging is made from the time offset and reference length and / or from the pressure / flow model and / or pressure / volume model of the blood vessel.

9. The method according to any one of claims 1 to 8,

characterized in that

the method steps are carried out independently of the platform, with an approximation to a standard resolution being obtained by varying the sampling rates of the pressure curve and the pulse wave signal (PW)

Comparability between different device-dependent

Recording techniques is performed.

10. Arrangement for performing a method according to one of the

preceding claims 1 to 9, comprising

a measuring sensor unit that can be inserted and placed in the blood vessel, an evaluation and storage unit (3) for recording, storing and

Processing of the pressure data recorded by the measuring sensor unit, a control and implemented in the evaluation and control unit

Evaluation program.

11. The arrangement according to claim 10,

characterized in that

the measuring sensor unit is designed as an indirect measuring sensor consisting of a catheter (1) which can be inserted invasively into the blood vessel and a pressure sensor (2).

12. Arrangement according to claim 10,

characterized in that

the evaluation and control unit (3) has an interface for connecting an EKG detection device (6).

13. Arrangement according to one of claims 10 to 12,

characterized in that

the evaluation and control unit (3) has a selection option for triggering a calibration and calibration process and / or for coordinating with the measurement sensor unit to be connected.